In the early days, content-based image retrieval (CBIR) was studied with global features.
Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively …

Logo detection has gradually become a research hotspot in the field of computer vision and
multimedia for its various applications, such as social media monitoring, intelligent …

In this paper we propose a method for logo recognition using deep learning. Our recognition
pipeline is composed of a logo region proposal followed by a Convolutional Neural Network …

Logo detection has been gaining considerable attention because of its wide range of
applications in the multimedia field, such as copyright infringement detection, brand visibility …

Text in natural images typically adds meaning to an object or scene. In particular, text
specifies which business places serve drinks (eg, cafe, teahouse) or food (eg, restaurant …

Logo detection in unconstrained images is challenging, particularly when only very sparse
labelled training images are accessible due to high labelling costs. In this work, we describe …

The bag-of-visual-words (BoW) model is effective for representing images and videos in
many computer vision problems, and achieves promising performance in image retrieval …

Existing logo detection benchmarks consider artificial deployment scenarios by assuming
that large training data with fine-grained bounding box annotations for each class are …

Food logo detection plays an important role in the multimedia for its wide real-world
applications, such as food recommendation of the self-service shop and infringement …

Existing logo detection methods usually consider a small number of logo classes and limited
images per class with a strong assumption of requiring tedious object bounding box …